条件和非自适应模型. 该方法在处理包括绳索、颗 粒介质、刚性盒子和布料在内的多种真实世界可变 形物体的预测和操控任务中表现出色. 神经辐射场 (Neural radiance field, NeRF)[106] 是一种用于 3D 场景表示和视图合成的深度学习方 法, 通过深度神经网络对场景的连续体积密度和颜 色进行建模, 能够从任意视角渲染出高质量的图像. 在文献 [107] 中研究人员提出了蒸馏特征场 for view synthesis. In: Proceedings of the 16th European Conference. Glasgow, UK: Springer, 2020. 106 Shen W, Yang G, Yu A L, Wong J, Kaelbling L P, Isola P. Distilled feature fields enable few-shot

..................................................................................................106 13.2 运营成本分析......................................................................................

........104 5.2 某银行智能客服案例........................................................................106 5.3 某银行欺诈检测案例........................................................................107 5.4 某银行投资管理案例

.104 7.1.1 性能指标..................................................................................106 7.1.2 用户反馈机制...........................................................................107 7.2 软件更新与模型再训练

部署与运维.............................................................................................106 11.1 部署环境准备..................................................................................107

104 9.1 部署环境准备....................................................................................106 9.2 系统安装与配置................................................................................109 9

......104 11.3 系统故障应急计划..........................................................................106 11.4 持续优化与更新..............................................................................108 12

..................................................................................................106 6.3 系统性能优化.......................................................................................

............104 6.1.1 硬件与软件兼容性...................................................................106 6.1.2 API 接口设计............................................................................109 6.2

......104 4.3.1 数据更新频率...........................................................................106 4.3.2 模型在线学习策略...................................................................108 4.3.3 更新数据验证与审核